» Articles » PMID: 20395585

Heat-health Warning Systems: a Comparison of the Predictive Capacity of Different Approaches to Identifying Dangerously Hot Days

Overview
Specialty Public Health
Date 2010 Apr 17
PMID 20395585
Citations 46
Authors
Affiliations
Soon will be listed here.
Abstract

Objectives: We compared the ability of several heat-health warning systems to predict days of heat-associated mortality using common data sets.

Methods: Heat-health warning systems initiate emergency public health interventions once forecasts have identified weather conditions to breach predetermined trigger levels. We examined 4 commonly used trigger-setting approaches: (1) synoptic classification, (2) epidemiologic assessment of the temperature-mortality relationship, (3) temperature-humidity index, and (4) physiologic classification. We applied each approach in Chicago, Illinois; London, United Kingdom; Madrid, Spain; and Montreal, Canada, to identify days expected to be associated with the highest heat-related mortality.

Results: We found little agreement across the approaches in which days were identified as most dangerous. In general, days identified by temperature-mortality assessment were associated with the highest excess mortality.

Conclusions: Triggering of alert days and ultimately the initiation of emergency responses by a heat-health warning system varies significantly across approaches adopted to establish triggers.

Citing Articles

The influence of air masses on human mortality in the contiguous United States.

Lee C, Silva A, Ibebuchi C, Sheridan S Int J Biometeorol. 2024; 68(11):2281-2296.

PMID: 39103651 PMC: 11519110. DOI: 10.1007/s00484-024-02745-y.


Temporal dynamic effects of meteorological factors and air quality on the physical health of the older adults in Shenzhen, China.

Jiang S, Han C, Ma Y, Ji J, Chen G, Guo Y Front Public Health. 2024; 12:1289253.

PMID: 38510362 PMC: 10951054. DOI: 10.3389/fpubh.2024.1289253.


Planning to Reduce the Health Impacts of Extreme Heat: A Content Analysis of Heat Action Plans in Local United States Jurisdictions.

Randazza J, Hess J, Bostrom A, Hartwell C, Adams Q, Nori-Sarma A Am J Public Health. 2023; 113(5):559-567.

PMID: 36926967 PMC: 10088945. DOI: 10.2105/AJPH.2022.307217.


Evaluating the Sensitivity of Heat Wave Definitions among North Carolina Physiographic Regions.

Puvvula J, Abadi A, Conlon K, Rennie J, Jones H, Bell J Int J Environ Res Public Health. 2022; 19(16).

PMID: 36011743 PMC: 9408726. DOI: 10.3390/ijerph191610108.


Internet searches and heat-related emergency department visits in the United States.

Adams Q, Sun Y, Sun S, Wellenius G Sci Rep. 2022; 12(1):9031.

PMID: 35641815 PMC: 9156736. DOI: 10.1038/s41598-022-13168-3.


References
1.
Moran D, Epstein Y . Evaluation of the environmental stress index (ESI) for hot/dry and hot/wet climates. Ind Health. 2006; 44(3):399-403. DOI: 10.2486/indhealth.44.399. View

2.
Tan J, Kalkstein L, Huang J, Lin S, Yin H, Shao D . An operational heat/health warning system in Shanghai. Int J Biometeorol. 2003; 48(3):157-62. DOI: 10.1007/s00484-003-0193-z. View

3.
Smoyer-Tomic K, Rainham D . Beating the heat: development and evaluation of a Canadian hot weather health-response plan. Environ Health Perspect. 2001; 109(12):1241-8. PMC: 1240506. DOI: 10.1289/ehp.011091241. View

4.
Pascal M, Laaidi K, Ledrans M, Baffert E, Caserio-Schonemann C, Le Tertre A . France's heat health watch warning system. Int J Biometeorol. 2005; 50(3):144-53. DOI: 10.1007/s00484-005-0003-x. View

5.
Bernard S, McGeehin M . Municipal heat wave response plans. Am J Public Health. 2004; 94(9):1520-2. PMC: 1448486. DOI: 10.2105/ajph.94.9.1520. View